1. Field of the Invention
The present invention relates to determination or mapping of reservoir pressure over a region of interest in a subsurface reservoir with integration of static bottom-hole pressure survey data and simulation modeling.
2. Description of the Related Art
In the oil and gas industries, massive amounts of data are required to be processed for computerized simulation, modeling and analysis for exploration and production purposes. For example, the development of underground hydrocarbon reservoirs typically includes development and analysis of computer simulation models of the reservoir. These underground hydrocarbon reservoirs are typically complex rock formations which contain both a petroleum fluid mixture and water. The reservoir fluid content usually exists in two or more fluid phases. The petroleum mixture in reservoir fluids is produced by wells drilled into and completed in these rock formations.
A computer reservoir model with realistic geological features and properties, appropriate distribution of in-situ fluids, as well as initial pressure conditions of the fluids also help in forecasting the optimal future oil and gas recovery from hydrocarbon reservoirs. Oil and gas companies have come to depend on such models as an important tool to enhance the ability to exploit a petroleum reserve.
It is desirable to be able to monitor pressure conditions in such a reservoir so that production is optimized. Adjustments can be made in production or injection rates to remove undesirable high or low pressure regions that might be observed from such monitoring. For reservoir planning purposes, the reservoir is simulated in a computer and runs are made of estimated production for a range of times over the projected life of the reservoir.
In simulation models, the reservoir is organized into a number of individual cells. Seismic data with increasing accuracy has permitted the cells to be on the order of 25 meters areal (x and y axis) intervals. For what are known as giant reservoirs, the number of cells is at least hundreds of millions, and reservoirs of what is known as giga-cell size (a billion cells or more) are encountered.
An example reservoir of the type for which production data are simulated over the expected reservoir life as illustrated by the model M (FIG. 1) is usually one which is known to those in the art as a giant reservoir. A giant reservoir may be several miles in length, breadth and depth in its extent beneath the earth and might, for example, have a volume or size on the order of three hundred billion cubic feet.
The reservoir is organized into a matrix which corresponds to the three dimensional extent of the reservoir and is composed of a number of contiguous 3-dimensional cells. It is common for a reservoir matrix to contain millions of cells to obtain as accurate an indication of reservoir conditions as feasible. Actual reservoir models may have several millions of such cells.
For reservoirs of this type, the actual number of wells may also be on the order of a thousand, with each well having a number of perforations into producing formations. Typically, not all of the wells in a reservoir have what are known as permanent downhole pressure gauges in them to monitor reservoir at those locations. This however represents a pressure measurement at only one point in the huge volume of the reservoir.
Thus, only a relatively small number of wells in a reservoir have such pressure gauges and as mentioned, the reservoir may have a substantial extent in terms of subsurface breadth, width and depth, leading to a very large number of cells in the model. The data points are extremely scarce when compared to the reservoir volume.
Therefore, the conditions and spatial quantity under which the actual well pressure is measured are completely different than the reservoir pressure which reservoir engineers are interested in for reservoir production optimization. Pressure measurements at the limited number of wells having gauges in the reservoir do not provide an accurate indication of reservoir pressure conditions of interest over the full 3-dimensional extent of the reservoir.
So far as is known, in previous isobaric mapping techniques, the well's static bottom-hole pressure (SBHP) readings were used to generate isobaric maps. Each SBHP reading was a control point based on which the isobaric map was generated. The interpolation between the control points was a simple linear interpolation that did not account for geological features or for reservoir dynamics during production.